Pub Date : 2017-04-01DOI: 10.1109/ICWR.2017.7959307
M. K. Nahari, Nasser Ghadiri, Zahra Jafarifard, A. B. Dastjerdi, J. Sack
The growth of semantic web technologies underpins the ever-increasing development of linked data and their applications. In recent years, the number of linked data sources has been raised from 12 to more than 2973 sets. The datasets are managed as decentralized sources, and their quality is a serious concern. The assessment of the quality of linked data is a key to adopting them in different fields because each data set has been developed by a different group, using various methods and tools. Moreover, crowd sourcing contributes as one of the main strategies in data collection. This contribution is seen in the tourism industry or E-commerce fields and deserves attention. The qualitative and quantitative diversity of such data is higher than those generated by official organizations and firms. In this paper, we first overview and evaluate the dimensions and measures for the quality assessment of data. Then, we present a novel framework as a solution for improving linked data quality evaluation and data fusion. Finally, we adopt several tools to assess the quality of data of some reputable data sources using the proposed framework.
{"title":"A framework for linked data fusion and quality assessment","authors":"M. K. Nahari, Nasser Ghadiri, Zahra Jafarifard, A. B. Dastjerdi, J. Sack","doi":"10.1109/ICWR.2017.7959307","DOIUrl":"https://doi.org/10.1109/ICWR.2017.7959307","url":null,"abstract":"The growth of semantic web technologies underpins the ever-increasing development of linked data and their applications. In recent years, the number of linked data sources has been raised from 12 to more than 2973 sets. The datasets are managed as decentralized sources, and their quality is a serious concern. The assessment of the quality of linked data is a key to adopting them in different fields because each data set has been developed by a different group, using various methods and tools. Moreover, crowd sourcing contributes as one of the main strategies in data collection. This contribution is seen in the tourism industry or E-commerce fields and deserves attention. The qualitative and quantitative diversity of such data is higher than those generated by official organizations and firms. In this paper, we first overview and evaluate the dimensions and measures for the quality assessment of data. Then, we present a novel framework as a solution for improving linked data quality evaluation and data fusion. Finally, we adopt several tools to assess the quality of data of some reputable data sources using the proposed framework.","PeriodicalId":304897,"journal":{"name":"2017 3th International Conference on Web Research (ICWR)","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129660318","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-04-01DOI: 10.1109/ICWR.2017.7959315
Sajjad Salehi, F. Taghiyareh
The study of social structure and the effect of it on social members is an attractive area in social networks. Structural balance theory focuses on patterns of signed links and frequency/popularity of them. In recent years several works try to define some approximations to calculate the distance of one unbalanced graph from nearest balanced one. But these works don't have any idea about the links with unstable signs that changing their sign makes the network more balanced. Also, some works introduce a centralized algorithm to detect these links. In this paper, we have introduced a localized algorithm for detecting and changing the sign of these links as a source of tension. The results of simulation for several scale-free networks with different features show that proposed algorithm has the ability to move the network to a balanced one. AS the proposed algorithm focuses on components of the social network to calculate localized measures, it is appropriate for agent-based models to study other social phenomena.
{"title":"A bottom-up algorithm to create structurally balanced social networks by modifying the sources of tension","authors":"Sajjad Salehi, F. Taghiyareh","doi":"10.1109/ICWR.2017.7959315","DOIUrl":"https://doi.org/10.1109/ICWR.2017.7959315","url":null,"abstract":"The study of social structure and the effect of it on social members is an attractive area in social networks. Structural balance theory focuses on patterns of signed links and frequency/popularity of them. In recent years several works try to define some approximations to calculate the distance of one unbalanced graph from nearest balanced one. But these works don't have any idea about the links with unstable signs that changing their sign makes the network more balanced. Also, some works introduce a centralized algorithm to detect these links. In this paper, we have introduced a localized algorithm for detecting and changing the sign of these links as a source of tension. The results of simulation for several scale-free networks with different features show that proposed algorithm has the ability to move the network to a balanced one. AS the proposed algorithm focuses on components of the social network to calculate localized measures, it is appropriate for agent-based models to study other social phenomena.","PeriodicalId":304897,"journal":{"name":"2017 3th International Conference on Web Research (ICWR)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128342213","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-04-01DOI: 10.1109/ICWR.2017.7959317
Behnam Hadi, M. Kargar
Today, much more than in the past are discussed of plagiarism in the research. Conditions of the Web and Possibility of complex and smart searches in a short time, is rated to this, and as a result has arrived significant damages to the research. Tools designed to deal with plagiarism act on the text and ignore images. On the other, an inseparable part of information transfer are images that transfer the large volume of information in an article or scientific research. Because of the images include a very wide range and especially found large amounts of flowchart images in the computer's texts, and as respects, flowcharts are carrying a lot of information, could be one of the options of plagiarism. The purpose of this paper is examine the plagiarism rate of a paper in terms of flowchart images plagiarism using artificial neural network. The average of flowchart images recognition accuracy in terms of structure, nodes and edges in the proposed method with 81.91 percent, indicating the success of this method.
{"title":"Plagiarism detection of flowchart images in the texts","authors":"Behnam Hadi, M. Kargar","doi":"10.1109/ICWR.2017.7959317","DOIUrl":"https://doi.org/10.1109/ICWR.2017.7959317","url":null,"abstract":"Today, much more than in the past are discussed of plagiarism in the research. Conditions of the Web and Possibility of complex and smart searches in a short time, is rated to this, and as a result has arrived significant damages to the research. Tools designed to deal with plagiarism act on the text and ignore images. On the other, an inseparable part of information transfer are images that transfer the large volume of information in an article or scientific research. Because of the images include a very wide range and especially found large amounts of flowchart images in the computer's texts, and as respects, flowcharts are carrying a lot of information, could be one of the options of plagiarism. The purpose of this paper is examine the plagiarism rate of a paper in terms of flowchart images plagiarism using artificial neural network. The average of flowchart images recognition accuracy in terms of structure, nodes and edges in the proposed method with 81.91 percent, indicating the success of this method.","PeriodicalId":304897,"journal":{"name":"2017 3th International Conference on Web Research (ICWR)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130152069","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-04-01DOI: 10.1109/ICWR.2017.7959306
Seyed Ali Mohammadi, Azam Andalib
The increasing volume of information about goods and services has been growing confusion for online buyers in cyberspace and this problem still continues. One of the most important ways to deal with the information overload is using a system called recommender system. The task of a recommender system is to offer the most appropriate and the nearest product to the user's demands and needs. In this system, one of the main problems is the cold start challenge. This problem occurs when a new user logs on and because there is no sufficient information available in the system from the user, the system won't be able to provide appropriate recommendation and the system error will rise. In this paper, we propose to use a new measurement called opinion leaders to alleviate this problem. Opinion leader is a person that his opinion has an impact on the target user. As a result, in the case of a new user logging in and the user — item's matrix sparseness, we can use the opinion of opinion leaders to offer the appropriate recommendation for new users and thereby increase the accuracy of the recommender system. The results of several conducted tests showed that opinion leaders combined with recommender systems will effectively reduce the recommendation errors.
{"title":"Using the opinion leaders in social networks to improve the cold start challenge in recommender systems","authors":"Seyed Ali Mohammadi, Azam Andalib","doi":"10.1109/ICWR.2017.7959306","DOIUrl":"https://doi.org/10.1109/ICWR.2017.7959306","url":null,"abstract":"The increasing volume of information about goods and services has been growing confusion for online buyers in cyberspace and this problem still continues. One of the most important ways to deal with the information overload is using a system called recommender system. The task of a recommender system is to offer the most appropriate and the nearest product to the user's demands and needs. In this system, one of the main problems is the cold start challenge. This problem occurs when a new user logs on and because there is no sufficient information available in the system from the user, the system won't be able to provide appropriate recommendation and the system error will rise. In this paper, we propose to use a new measurement called opinion leaders to alleviate this problem. Opinion leader is a person that his opinion has an impact on the target user. As a result, in the case of a new user logging in and the user — item's matrix sparseness, we can use the opinion of opinion leaders to offer the appropriate recommendation for new users and thereby increase the accuracy of the recommender system. The results of several conducted tests showed that opinion leaders combined with recommender systems will effectively reduce the recommendation errors.","PeriodicalId":304897,"journal":{"name":"2017 3th International Conference on Web Research (ICWR)","volume":"82 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114430514","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-04-01DOI: 10.1109/ICWR.2017.7959308
Amir Hossein Atashkar, Nasser Ghadiri, Mehdi Joodaki
RDF models are widely used in the web of data due to their flexibility and similarity to graph patterns. Because of the growing use of RDFs, their volumes and contents are increasing. Therefore, processing of such massive amount of data on a single machine is not efficient enough, because of the response time and limited hardware resources. A common approach to overcome this limitation is cluster processing and huge datasets could benefit distributed cluster processing on Apache Hadoop. Because of using too much of hard disks, the processing time is usually inadequate. In this paper, we propose a partitiong approach based on Apache Spark for rapid processing of RDF data models. A key feature of Apache Spark is using main memory instead of hard disk, so the speed of data processing in our method is improved. We have evaluated the proposed method by runing SQL queris on RDF data which partitioned on the cluster and demonstrates improved performance.
{"title":"Linked data partitioning for RDF processing on Apache Spark","authors":"Amir Hossein Atashkar, Nasser Ghadiri, Mehdi Joodaki","doi":"10.1109/ICWR.2017.7959308","DOIUrl":"https://doi.org/10.1109/ICWR.2017.7959308","url":null,"abstract":"RDF models are widely used in the web of data due to their flexibility and similarity to graph patterns. Because of the growing use of RDFs, their volumes and contents are increasing. Therefore, processing of such massive amount of data on a single machine is not efficient enough, because of the response time and limited hardware resources. A common approach to overcome this limitation is cluster processing and huge datasets could benefit distributed cluster processing on Apache Hadoop. Because of using too much of hard disks, the processing time is usually inadequate. In this paper, we propose a partitiong approach based on Apache Spark for rapid processing of RDF data models. A key feature of Apache Spark is using main memory instead of hard disk, so the speed of data processing in our method is improved. We have evaluated the proposed method by runing SQL queris on RDF data which partitioned on the cluster and demonstrates improved performance.","PeriodicalId":304897,"journal":{"name":"2017 3th International Conference on Web Research (ICWR)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133949170","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-04-01DOI: 10.1109/ICWR.2017.7959318
Maryam Tasviri, S. Golpayegani, Hoda Ghavamipoor
This study presents a model offering people which food is healthier and makes them more satisfied based on their moods and food consumption behaviors. The social network analysis techniques are applied on the food consumption of the people whom were recorded in information systems. The implementation method is according to this procedure: first, people classified to 6 groups based on their nutrition style getting from the Islamic traditional medicine and some previous papers in the modern medicine. Then, a data network was made from people's relationships. Afterwards, a model has been presented based on the analysis of that network. To evaluate this model, the proposed method is applied on a university's self-service restaurant system. The results show that people with a healthy or "hot and wet" temperament nutrition style, have personality traits of "extraversion", "openness" and "conscientiousness". Moreover, people with a traditional nutrition style or "cold and wet" temperament nutrition, are people with personality traits of "introversion" and "neuroticism".
{"title":"Presenting a model based on social network analysis in order to offer a diet to users proper to their mood","authors":"Maryam Tasviri, S. Golpayegani, Hoda Ghavamipoor","doi":"10.1109/ICWR.2017.7959318","DOIUrl":"https://doi.org/10.1109/ICWR.2017.7959318","url":null,"abstract":"This study presents a model offering people which food is healthier and makes them more satisfied based on their moods and food consumption behaviors. The social network analysis techniques are applied on the food consumption of the people whom were recorded in information systems. The implementation method is according to this procedure: first, people classified to 6 groups based on their nutrition style getting from the Islamic traditional medicine and some previous papers in the modern medicine. Then, a data network was made from people's relationships. Afterwards, a model has been presented based on the analysis of that network. To evaluate this model, the proposed method is applied on a university's self-service restaurant system. The results show that people with a healthy or \"hot and wet\" temperament nutrition style, have personality traits of \"extraversion\", \"openness\" and \"conscientiousness\". Moreover, people with a traditional nutrition style or \"cold and wet\" temperament nutrition, are people with personality traits of \"introversion\" and \"neuroticism\".","PeriodicalId":304897,"journal":{"name":"2017 3th International Conference on Web Research (ICWR)","volume":"91 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133108212","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-04-01DOI: 10.1109/ICWR.2017.7959303
Fatemeh Talebzadeh Pirvadlu, Ghodrat Sepidnam
Vulnerabilities in web applications are due to various factors. Failure to properly validated user input is one of the factors that led to run unauthorized code in these programs. Sqli and Xss are two common vulnerabilities in web applications, That is due to lack of proper input validation. Therefore, in this paper we study how to protect organizational websites of north khorasan in iran against Sqli and Xss vulnerabilities. We have analyzed eleven websites. Ten of which related to government organizations and one of them is from private organization. These Web sites have been tested with licenses taken from the relevant organizations.
{"title":"Assessments Sqli and Xss vulnerability in several organizational websites of North khorasan in Iran and offer solutions to fix these vulnerabilities","authors":"Fatemeh Talebzadeh Pirvadlu, Ghodrat Sepidnam","doi":"10.1109/ICWR.2017.7959303","DOIUrl":"https://doi.org/10.1109/ICWR.2017.7959303","url":null,"abstract":"Vulnerabilities in web applications are due to various factors. Failure to properly validated user input is one of the factors that led to run unauthorized code in these programs. Sqli and Xss are two common vulnerabilities in web applications, That is due to lack of proper input validation. Therefore, in this paper we study how to protect organizational websites of north khorasan in iran against Sqli and Xss vulnerabilities. We have analyzed eleven websites. Ten of which related to government organizations and one of them is from private organization. These Web sites have been tested with licenses taken from the relevant organizations.","PeriodicalId":304897,"journal":{"name":"2017 3th International Conference on Web Research (ICWR)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125882394","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-04-01DOI: 10.1109/ICWR.2017.7959300
Erfan Farhangi, Nasser Ghadiri, Mahsa Asadi, M. Nikbakht, Sylvain Pitre
In recent years, we are faced with large amounts of sporadic unstructured data on the web. With the explosive growth of such data, there is a growing need for effective methods such as clustering to analyze and extract information. Biological data forms an important part of unstructured data on the web. Protein sequence databases are considered as a primary source of biological data. Clustering can help to organize sequences into homologous and functionally similar groups and can improve the speed of data processing and analysis. Proteins are responsible for most of the activities in cells. The majority of proteins show their function through interaction with other proteins. Hence, prediction of protein interactions is an important research area in the biomedical sciences. Motifs are fragments frequently occurred in protein sequences. A well- known method to specify the protein interaction is based on motif Clustering. Existing works on motif clustering methods share the problem of limitation in the number of clusters. However, regarding the vast amount of motifs and the necessity of a large number of clusters, it seems that an efficient, scalable and fast method is necessary to cluster such large number of sequences. In this paper, we propose a novel approach to cluster a large number of motifs. Our approach includes extracting motifs within protein sequences, feature selection, preprocessing, dimension reduction and utilizing BigFCM (a large-scale fuzzy clustering) on several distributed nodes with Hadoop framework to take the advantage of MapReduce Programming. Experimental Results show very good Performance of our approach.
{"title":"Fast and scalable protein motif sequence clustering based on Hadoop framework","authors":"Erfan Farhangi, Nasser Ghadiri, Mahsa Asadi, M. Nikbakht, Sylvain Pitre","doi":"10.1109/ICWR.2017.7959300","DOIUrl":"https://doi.org/10.1109/ICWR.2017.7959300","url":null,"abstract":"In recent years, we are faced with large amounts of sporadic unstructured data on the web. With the explosive growth of such data, there is a growing need for effective methods such as clustering to analyze and extract information. Biological data forms an important part of unstructured data on the web. Protein sequence databases are considered as a primary source of biological data. Clustering can help to organize sequences into homologous and functionally similar groups and can improve the speed of data processing and analysis. Proteins are responsible for most of the activities in cells. The majority of proteins show their function through interaction with other proteins. Hence, prediction of protein interactions is an important research area in the biomedical sciences. Motifs are fragments frequently occurred in protein sequences. A well- known method to specify the protein interaction is based on motif Clustering. Existing works on motif clustering methods share the problem of limitation in the number of clusters. However, regarding the vast amount of motifs and the necessity of a large number of clusters, it seems that an efficient, scalable and fast method is necessary to cluster such large number of sequences. In this paper, we propose a novel approach to cluster a large number of motifs. Our approach includes extracting motifs within protein sequences, feature selection, preprocessing, dimension reduction and utilizing BigFCM (a large-scale fuzzy clustering) on several distributed nodes with Hadoop framework to take the advantage of MapReduce Programming. Experimental Results show very good Performance of our approach.","PeriodicalId":304897,"journal":{"name":"2017 3th International Conference on Web Research (ICWR)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123952299","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-04-01DOI: 10.1109/ICWR.2017.7959313
F. Ebadifard, S. M. Babamir
Cloud computing employs parallel and distributed computing concepts to provide users with shared resources through the internet. One of the most important issues which are raised in a cloud environment is task scheduling on existing resources; so that on the one hand it can provide user's requirements, such as minimum run time or cost and on the other hand with the proper use of resources, can also cause service providers' benefits. In this paper we extended a recent heuristic algorithm called Black hole Optimization (BHO) and present a multi objective scheduling method for workflow application based on Pareto optimizer algorithm. Our proposed method can consider user requirements and also the interests of service providers. Using the balanced and unbalanced workflow we compared our proposed method with algorithms of SPEA2 and NSGA2 based on the parameters of completion time and cost and resource efficiency.
{"title":"Optimizing multi objective based workflow scheduling in cloud computing using black hole algorithm","authors":"F. Ebadifard, S. M. Babamir","doi":"10.1109/ICWR.2017.7959313","DOIUrl":"https://doi.org/10.1109/ICWR.2017.7959313","url":null,"abstract":"Cloud computing employs parallel and distributed computing concepts to provide users with shared resources through the internet. One of the most important issues which are raised in a cloud environment is task scheduling on existing resources; so that on the one hand it can provide user's requirements, such as minimum run time or cost and on the other hand with the proper use of resources, can also cause service providers' benefits. In this paper we extended a recent heuristic algorithm called Black hole Optimization (BHO) and present a multi objective scheduling method for workflow application based on Pareto optimizer algorithm. Our proposed method can consider user requirements and also the interests of service providers. Using the balanced and unbalanced workflow we compared our proposed method with algorithms of SPEA2 and NSGA2 based on the parameters of completion time and cost and resource efficiency.","PeriodicalId":304897,"journal":{"name":"2017 3th International Conference on Web Research (ICWR)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129266158","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-04-01DOI: 10.1109/ICWR.2017.7959304
M. Mahmoudi, M. Azimzade, M. Esnaashari, M. Farhoodi, Reza Badie
Nowadays, search engines are prominent tools, which are required by users, for finding information in web. Multimedia search engines are of special importance due to two different reasons; 1) attractiveness of multimedia contents and 2) growing rate of the creation and online dissemination of such contents. In this paper every effort is made to analyze and recognize the propensities of the users of Persian multimedia search services. For this purpose, behaviors of Iranian users of Parsijoo's image, voice and video search services has been studied by analyzing its usage log files. The analyses, which have been carried out by using users' queries for a time period of three months, can be categorized into two distinct types; holistic analyses and the ones based on using frequently used queries. The results of the analyses have shown that users are mostly after entertainments and amusement topics when they use multimedia search services.
{"title":"Persian multimedia search services' users propensities","authors":"M. Mahmoudi, M. Azimzade, M. Esnaashari, M. Farhoodi, Reza Badie","doi":"10.1109/ICWR.2017.7959304","DOIUrl":"https://doi.org/10.1109/ICWR.2017.7959304","url":null,"abstract":"Nowadays, search engines are prominent tools, which are required by users, for finding information in web. Multimedia search engines are of special importance due to two different reasons; 1) attractiveness of multimedia contents and 2) growing rate of the creation and online dissemination of such contents. In this paper every effort is made to analyze and recognize the propensities of the users of Persian multimedia search services. For this purpose, behaviors of Iranian users of Parsijoo's image, voice and video search services has been studied by analyzing its usage log files. The analyses, which have been carried out by using users' queries for a time period of three months, can be categorized into two distinct types; holistic analyses and the ones based on using frequently used queries. The results of the analyses have shown that users are mostly after entertainments and amusement topics when they use multimedia search services.","PeriodicalId":304897,"journal":{"name":"2017 3th International Conference on Web Research (ICWR)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121269751","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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